Michela Cortini, University G. d'Annunzio of Chieti – Pescara

Teresa Galanti, University G. d'Annunzio of Chieti – Pescara

Marco Giovanni Mariani, University of Bologna

This special issue examines how artificial intelligence is transforming recruitment and selection practices in organizations. While AI technologies such as automated screening, video interview analytics, and generative AI tools offer efficiency gains, they simultaneously raise critical concerns regarding fairness, transparency, accountability, and ethics. The collection seeks contributions that explore both the opportunities and challenges of AI-mediated selection from multiple perspectives.

The special issue invites theoretical, empirical, methodological, and review contributions addressing the human-AI interface in recruitment and selection. Research should consider how AI affects applicants' and recruiters' experiences, perceptions of procedural justice, and organizational attractiveness. The editors particularly welcome work bridging theory and practice to help organizations implement AI-enabled selection responsibly and effectively.

Appel publié par International Journal of Selection and Assessment. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Applicants' and recruiters' motivational and emotional reactions to AI
• Algorithmic decision-making and perceptions of fairness, trust, and justice
• Transparency, explainability, and human oversight in selection
• Human-AI collaboration in personnel selection
• AI-enabled game-based and adaptive assessment methods
• Bias mitigation and diversity enhancement in AI recruitment
• Ethical, legal, and regulatory perspectives on AI in hiring
• Motivational theories in AI-mediated selection
• Impact of AI on recruiters' professional identity and autonomy
• Generative AI in employer branding and recruitment marketing
• Methodological innovations for studying AI-human interaction
• AI influence on candidate experience and authenticity
• Development and validation of AI-supported assessment tools

Timeline

• October 20, 2026: Initial manuscript submission period begins
• January 31, 2027: Initial manuscript submission period ends
• May 1, 2027: First round of reviews ends; revision and resubmission period begins
• August 1, 2027: Revision and resubmission period ends; second round of reviews begins
• October 1, 2027: Second round of reviews ends
• January 15, 2028: Final submissions

Raffaele Ciriello, The University of Sydney Business School

Martin Adam, University of Goettingen

Zhongyun Zhou, Tongji University

AI companions are conversational systems designed to simulate human-like relationships and deployed as emotional support tools, tutors, and therapeutic assistants. Unlike conventional productivity software, their value derives from sustained interaction and personalised continuity, raising questions about trust, dependency, wellbeing, and how relational dynamics emerge through interactions between users, systems, and contexts.

This special issue invites Information Systems scholarship to examine AI companions through a relational lens extending beyond efficiency metrics. While these systems offer potential benefits such as broadened access to support, they simultaneously raise concerns about surveillance, manipulation, and commodified intimacy, reshaping individual capabilities and organisational practices.

The special issue welcomes theoretically ambitious and empirically grounded research across diverse methodologies that carefully theorise the sociotechnical characteristics of relational AI systems. Submissions should address design, governance, and use implications, with particular interest in interdisciplinary and critical perspectives.

Appel publié par Information Systems Journal. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Dark sides of AI companions, problematic use patterns, and their potential roles in fostering delusions, harmful ideation, and maladaptive dependencies
• Relational perspectives on digital technologies: extending beyond instrumental and performance-based evaluation
• Social presence, parasocial interaction, and relationship formation with AI systems
• Anthropomorphism as a sociotechnical phenomenon: design, effects, and risks
• Design principles for AI systems that promote dignity, autonomy, trust, and human flourishing
• Hyper-personalisation and interaction-level adaptation in AI-mediated relationships
• How AI companions affect loneliness, wellbeing, identity formation, and social connection
• Human transformation through AI interaction: cognition, creativity, identity, and capability development
• Dependency, attachment, persuasion, and behavioural influence in sustained human–AI interaction
• Tensions and paradoxes in human–AI relationships
• AI companions in organisations, including changing work practices, expertise, authority, and control
• AI companions in healthcare, education, customer service, and public services: opportunities and risks
• Platform incentives, business models, and governance logics shaping relational AI
• Alternative governance and ownership models, including cooperative, open-source, and public-interest approaches
• Governance of emotionally sensitive data, privacy, portability, and consent
• Power asymmetries between users, providers, employers, and states in relational AI
• Youth, ageing populations, and other vulnerable stakeholders of relational AI
• Cross-cultural differences in companionship, intimacy, and acceptable machine roles
• Dual-use concerns, including manipulation, radicalisation, fraud, coercion, and political influence
• Regulatory and policy approaches to companion AI and socially consequential AI infrastructures
• Historical, philosophical, feminist, or critical perspectives on human–AI relations

Timeline

• December 31, 2026: Extended abstract submission deadline (optional)
• March 31, 2027: Full paper submission deadline

Associate editors

• Anuragini Shirish, IMT Business School
• Arisa Shollo, Copenhagen Business School
• Stan Karanasios, University of Queensland
• Sven Laumer, Friedrich-Alexander University
• Angsana Techatassanasoontorn, Auckland University of Technology
• Christoph Breidbach, University of Queensland
• Hameed Chughtai, Lancaster University
• Evelyn Ng, University of Sydney
• Johan Sæbø, University of Oslo
• Brad McKenna, Norwich Business School
• Riitta Hekkala, Aalto University
• Kai Riemer, University of Sydney
• Dimitra Petrakaki, University of Sussex
• Avijit Sengupta, University of Queensland

Louis Tay, Purdue University

Sarah Bankins, Macquarie University

Markus Langer, University of Freiburg

This special issue examines how generative AI is reshaping the subjective experience of work across individuals, teams, and organizations. Rather than focusing on technical capabilities, it centers on what it feels like to work with AI systems like ChatGPT and Claude—how these tools influence engagement, relationships, identity, and organizational norms as adoption rapidly increases among knowledge workers worldwide.

The issue seeks empirically rigorous, theory-grounded research that closely observes generative AI in actual workplace settings. Priority is given to field research within organizations, implementation studies tracking deployment experiences, longitudinal designs, and rigorous qualitative research. Vignette studies, cross-sectional surveys of convenience samples, and conceptual papers without data are out of scope.

Submissions should articulate theoretical mechanisms for how generative AI changes work experiences, provide evidence credible for practitioners, and explicitly discuss practical impact for employees, managers, HR leaders, and policymakers.

Appel publié par Personnel Psychology. Voir l'appel sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Experience of work: Cognitive offloading and changes in effort, flow, and engagement; experiences of autonomy, competence, and ownership over AI-generated or AI-assisted output; changes to the meaning of work; skill development versus skill atrophy; work intensification versus work-life balance; changing nature of expertise; calibration of trust and over- or under-reliance; professional identity as roles shift
• Workplace relationships: Generative AI as a team member and its impact on social and working dynamics; emerging disclosure norms; trust, attribution, and competence judgments when AI is involved; migration of help-seeking and sensemaking from colleagues to AI tools; effects on collaboration, collegiality, reciprocity, informal mentorship, and organizational cohesion
• Training and development: Use and experience of AI as a trainer, coach, and mentor; development and declines in knowledge, skills, and abilities with AI use; lasting effects of AI-based training; comparisons of human trainers versus AI trainers; design of AI-based training and transfer to job performance
• Leadership: Leaders' use of generative AI for communication and the authenticity dilemma of machine-mediated empathy, vision, and feedback; leader decision processes with AI input; generative AI systems operating autonomously or in hybrid arrangements; what it feels like to be managed by generative AI
• Organizational culture: Emergent norms of acceptable generative AI use; psychological safety around disclosing versus concealing use; experience of monitoring and surveillance of workers' AI use or non-use; equity and felt divide between users and non-users; implications for inclusive workplaces

Timeline

• August 1, 2027: Submission window opens
• August 27, 2027: Submission deadline
• August 31, 2027: Submission window closes

Muhammad Imran Rasheed, University of Surrey

Barbara Rita Barricelli, Università degli Studi di Brescia

Waseem Ul Hameed, Universiti Utara Malaysia

This special issue examines how artificial intelligence systems are transforming workplace interactions, employee behavior, and organizational dynamics. While prior research has focused on AI adoption and performance outcomes, this collection addresses the human-centered dimensions of AI at work, including how employees develop trust in intelligent systems, experience AI-mediated processes, adapt their behaviors, and navigate issues such as technostress, autonomy, and cognitive load.

The special issue prioritizes behavioral, cognitive, and psychological perspectives on human-AI interaction in organizational settings. It seeks contributions that explore employee experiences with intelligent technologies, design of user-centered AI systems, transparency mechanisms, and the creation of psychologically sustainable digital work environments. The collection welcomes empirical, theoretical, and design-oriented research across quantitative, qualitative, and mixed-method approaches.

Appel publié par Behaviour & Information Technology. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Employee interaction with AI-enabled systems
• Human reliance, overreliance, and resistance toward AI
• Behavioral adaptation to intelligent technologies
• Human-AI collaboration and hybrid decision-making
• Trust formation in intelligent systems
• Algorithmic transparency and explainable AI
• Employee perceptions of AI fairness and accountability
• Behavioral responses to opaque decision systems
• Technostress, digital exhaustion, and AI fatigue
• Cognitive overload and information processing under AI systems
• AI dependency and employee wellbeing
• Digital distraction and attention fragmentation
• AI-supported autonomy and employee empowerment
• Algorithmic management and behavioral control
• Digital surveillance and monitoring technologies
• Behavioral consequences of automated performance systems
• Ethical design of workplace AI systems
• Human-centered intelligent systems
• Responsible AI implementation in organizations
• Designing psychologically sustainable digital work environments
• AI-enabled learning systems and digital upskilling
• Employee agility and adaptability in AI-enabled workplaces
• Behavioral implications of reskilling and task transformation
• Human learning behavior in technology-mediated contexts
• AI-supported teamwork and collaboration
• Virtual collaboration and intelligent communication systems
• Social interaction patterns in AI-mediated environments
• Team trust and coordination under intelligent systems
• AI in healthcare, hospitality, education, finance, and public services
• Gig work, platform labor, and digital employment systems
• Cross-cultural and cross-national comparisons
• Remote and hybrid work environments
• User experience (UX) of workplace AI systems
• Human-centered design of intelligent workplace technologies
• Conversational AI and intelligent assistants at work
• Adaptive and personalized workplace interfaces
• AI usability and user acceptance in organizational settings
• Interaction design for human-AI collaboration
• Human oversight and human-in-the-loop systems
• Trust calibration in intelligent systems
• Employee engagement with AI-enabled technologies
• Interface design for responsible and ethical AI use
• User perceptions of agency, control, and autonomy in AI-mediated work environments

Timeline

• July 31, 2027: Manuscript deadline

Asha Thomas, Wrocław University of Science and Technology

Moreno Frau, Corvinus University of Budapest

Dominyka Venciūtė, ISM University of Management and Economics

Across contemporary organizations, advances in artificial intelligence (AI) are transforming AI from a discrete technological resource into a systemic organizational capability that actively shapes decision-making, business model innovation, and competitive advantage. Traditionally, AI interfaces have largely been reactive, responding to human prompts and predefined inputs. The emergence of Agentic Artificial Intelligence represents a fundamental shift, as agentic systems are designed to operate with increasing autonomy, enabling goal-driven planning, workflow orchestration, coordination across systems, and machine-initiated action with limited human intervention.

Appel publié par Journal of Enterprise Information Management. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• How does Agentic AI enable new forms of value creation, capture, and measurement in organizations? Under what conditions can agentic systems also lead to value co-destruction or unintended negative outcomes due to misaligned autonomy, resource integration, or decision logic?
• How do organizations design governance, accountability, trust, and regulatory compliance mechanisms for Agentic AI systems operating with increasing autonomy? What challenges arise when human oversight is limited or distributed across functions?
• How do ethical considerations, responsibility, and moral agency evolve when AI systems act as semi-autonomous organizational actors rather than decision-support tools?
• How does Agentic AI reshape business process redesign, orchestration, and automation across organizational functions such as marketing, human resource management, operations, finance, and customer engagement?
• In what ways is artificial intelligence becoming normalized within organizational and marketing practice, shifting from experimental adoption to routinized, AI-embedded decision-making and workflows?
• How does Agentic AI influence workforce transformation, the future of work, and human resource management practices, including recruitment, performance evaluation, learning, and employee autonomy?
• How does the adoption of Agentic AI differ across organizational contexts, such as small and medium-sized enterprises versus large corporations, and what factors shape successful implementation and impact?
• How do emotional, relational, and interactional dynamics shape human–AI engagement in Agentic AI–driven sales, marketing, and customer experience contexts?
• How can human–AI collaboration and human-in-the-loop design be sustained when AI systems increasingly initiate actions, coordinate tasks, and learn autonomously?
• How do multi-agent systems, coordination mechanisms, and organizational architectures evolve as multiple human and artificial agents interact within complex socio-technical environments?
• How can existing theories of agency, organizational learning, and socio-technical systems be extended or reconfigured to explain machine agency and autonomous action in Agentic AI–enabled organizations?
• How does Agentic AI transform knowledge management, organizational learning, and decision support by enabling systems that not only retrieve and integrate knowledge but also reason, adapt, and act upon it?

Timeline

• March 1, 2026: Opening date for manuscript submissions
• September 30, 2026: Closing date for manuscript submissions

Mark Camilleri, University of Malta

Generative Artificial Intelligence (GenAI) and Agentic Artificial Intelligence (Agentic AI) are transforming how services are designed, delivered, experienced and led. While GenAI refers to systems, such as large language models (LLMs), that produce content in response to human prompts; Agentic AI technologies may be considered as active agents that can implement tasks (rather than merely functioning as passive generators). The latter can monitor situations, allocate resources, initiate and manage processes as well as co-ordinate multiple activities. Hence, Agentic AI algorithms and their governance affect service outcomes.

Appel publié par Journal of Services Marketing. Lire l'appel complet sur le site de l'éditeur. Fiche de l'appel sur kerostig.

Potential topics

• Theoretical perspectives on Generative and Agentic AI adoption in service environments
• Comparative or multi-theoretical frameworks for studying human-AI interaction in services
• Anthropomorphism, social presence and human-AI relationships
• Perceived affordances, interface design and service experiences
• Emotions, expectations and psychological responses to AI
• Adoption, acceptance and continued use of AI in services
• Trust, ethics, accountability and relational governance
• AI as a service actor within socio-technical systems
• Contextual and contingency-based perspectives
• Value co-creation, value co-destruction and service outcomes
• Organizational, strategic and policy implications of Generative and Agentic AI in services

Timeline

• June 23, 2026: Opening date for manuscripts submissions
• February 26, 2027: Closing date for manuscripts submission